Comprehensive Survey on Techniques for Improving Cross-Lingual Alignment in Multilingual Language Models

Cross-lingual alignment, the meaningful similarity of representations across languages in multilingual language models, is crucial for zero-shot cross-lingual transfer. This survey provides a comprehensive overview of techniques to improve cross-lingual alignment, including objectives using parallel data, contrastive learning, modified pre-training schemes, adapter tuning, and data augmentation.